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Title page for ETD etd-07122006-111755


Type of Document Master's Thesis
Author Benincasa, Anne Browning
URN etd-07122006-111755
Title Feasibility Study for Image-Guided Kidney Surgery: Assessment of Required Intraoperative Surface for Accurate Physical to Image Space Registrations
Degree Master of Science
Department Biomedical Engineering
Advisory Committee
Advisor Name Title
Robert L Galloway Committee Chair
Michael I Miga Committee Co-Chair
Keywords
  • surface-based registrations
  • laser range scan
  • nephrectomy
  • image-guided kidney surgery
Date of Defense 2006-08-11
Availability unrestricted
Abstract
A notable complication of applying current image-guided surgery techniques of soft tissue to kidney resections (nephrectomies) is the limited field of view of the intraoperative kidney surface. This limited view constrains the ability to obtain a geometrically descriptive surface for accurate surface-based registrations. Examining the affects of the limited view involved using two orientations of a kidney phantom to model typical laparoscopic and open partial nephrectomy views. Point-based registrations, using either rigidly attached markers or anatomical landmarks as fiducials, served as initial alignments for surface-based registrations. Laser range scanner (LRS) obtained surfaces were registered to the phantom's image surface using a rigid iterative closest point algorithm. Subsets of each orientation’s LRS surface were used in a robustness test to determine which parts of the surface can accurately predict registrations for the entire surface. Results suggest that obtaining accurate registrations is a function of the percentage of the total surface and of geometric surface properties, such as curvature. Approximately 30% of the total image surface is required, regardless of the location of that surface subset. However, that percentage decreases when the surface subset contains information from opposite ends of the surface and/or unique anatomical features, such as the renal artery and vein. Thus, under optimal conditions, such as maximized visible surface, image-guided kidney surgery is feasible.
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